Chaotic population dynamics favors the evolution of dispersal
Chaotic population dynamics favors the evolution of dispersal
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DOI：
10.1086/285949
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发表时间：
1996-10-01
影响因子：
2.9
通讯作者：
Mcpeek, MA
中科院分区：
文献类型：
--
作者：
Holt, RD;Mcpeek, MA
扩散——种群之间的移动——是大多数生物体生物学的一个核心特征。有大量关于生态学和扩散进化的文献（例如，Swingland 和 Greenwood 1986）。许多理论研究探索了有利于扩散进化的因素，包括亲属之间的竞争和近亲繁殖效应（例如，Hamilton and May 1977；Comins 1982；Frank 1986；Taylor 1988；Wiener and Feldman 1991），外在产生的时空异质性的影响（Gadgil 1971；Roff 1975；Metz 等人，2015）。 1983；Levin 等人 1984；Cohen 和 Levin 1991），以及群体内和群体间选择的相互作用（Kuno 1981；Olivieri 等人 1995）。已经证明（Hastings 1983；Holt 1985），如果个体以固定的人均比率在具有局部密度依赖性的地点之间分散，那么，在没有时间异质性的情况下，仅仅依靠丰度的空间异质性就无法选择分散（另见 Liberman 和 Feldman 1989）。原因是，如果栖息地的承载能力 K 不同，则个体从高 K 斑块流向低 K 斑块的不对称流动（Holt 1985）。反过来，这种流动会降低高 K 斑块的密度（增加那里的适应度），同时增加低 K 斑块的密度（降低那里的适应度）。因为分散基本上是使个体的适应度下降，所以平均而言，分散在空间（但不是时间）异质环境中是不利的。这些理论结果强调了时间异质性对于有利于扩散的重要性。在开放斑块的集合种群中，如果斑块之间的适应度排序随时间变化，则分散可能具有选择性优势（Bull 等人，1987）。分散实际上提供了一种进化策略，允许个体利用适应性的时空变化。时间变异性和扩散之间关系的理论预期与自然种群的一些数据相匹配（Roff 1990）。我们之前研究了一个简单的两块离散生成模型，其中个体以恒定速率在两个块之间分散，并在每个块中经历了密度依赖性（McPeek 和 Holt 1992）。我们发现，与密度无关的增长率的时间变化（各斑块之间部分不相关）有利于扩散。此外，如果两个斑块是异质的（具有不同的承载能力），则可以稳定地维持分散率的多态性。其他作者也表明，分散多态性可能在时间和空间异质环境中得以维持（Frank 1986；Cohen 和 Levin 1991；Karlson 和 Taylor 1992）。在这篇文章中，我们证明了在其他方面的混沌种群动态
Dispersal-movement between populations-is a central feature in the biology of most organisms. There is an enormous literature on the ecology and evolution of dispersal (eg, Swingland and Greenwood 1986). Many theoretical studies have explored factors favoring the evolution of dispersal, including competition among kin and inbreeding effects (eg, Hamilton and May 1977; Comins 1982; Frank 1986; Taylor 1988; Wiener and Feldman 1991), the influences of extrinsically generated, spatiotemporal heterogeneity (Gadgil 1971; Roff 1975; Metz et al. 1983; Levin et al. 1984; Cohen and Levin 1991), and the interplay of withinpopulation and between-population selection (Kuno 1981; Olivieri et al. 1995). It has been demonstrated(Hastings 1983; Holt 1985) that if individuals disperse at fixed per capita rates between sites with local density dependence, then, without emporal heterogeneity, spatial heterogeneity in abundance alone is unable to select for dispersal (see also Liberman and Feldman 1989). The reason is that if habitats vary in carrying capacity, K, there is an asymmetric flow of individuals from high-K to low-K patches (Holt 1985). Such flow, in turn, reduces density in high-K patches (increasing fitness there) while increasing density in low-K patches (depressing fitness there). Because dispersal is basically moving individuals down gradients in fitness, on average, dispersal is disfavored in spatially (but not temporally) heterogeneous environments. These theoretical results highlight the importance of temporal heterogeneity in favoring dispersal. In a metapopulation of open patches, if the rank order of fitness among patches varies through time, dispersal can be selectively advantageous (Bull et al. 1987). Dispersal in effect provides an evolutionary strategy that permits individuals to exploit spatiotemporal variation in fitness. The theoretical expectation of a relation between temporal variability and dispersal matches some data from natural populations (Roff 1990).We previously examined a simple two-patch, discrete-generation model in which individuals dispersed at constant rates between two patches and experienced density dependence in each patch (McPeek and Holt 1992). We showed that temporal variation in density-independent growth rates, partially uncorrelated across patches, favored dispersal. Moreover, a polymorphism in dispersal rates could be stably maintained if the two patches were heterogeneous (with different carrying capacities). Other authors have also shown that dispersal polymorphisms may be maintained in temporally and spatially heterogeneous environments (Frank 1986; Cohen and Levin 1991; Karlson and Taylor 1992). In this note, we demonstrate that chaotic population dynamics in otherwise